High-resolution measurements of face-to-face contact patterns in a primary school

TL;DR

This study quantitatively characterizes face-to-face contact patterns among primary school children and teachers using radio frequency identification, providing detailed data crucial for modeling disease transmission and informing public health strategies.

Contribution

It presents the first detailed, time-resolved contact network data in a primary school, revealing structured interaction patterns relevant for epidemic modeling.

Findings

Children have an average of 323 contacts per day with 47 peers.

Most contacts are within the same class, with children spending three times more time with classmates.

The contact network exhibits class and age structures that differ from homogeneous mixing assumptions.

Abstract

Little quantitative information is available on the mixing patterns of children in school environments. Describing and understanding contacts between children at school would help quantify the transmission opportunities of respiratory infections and identify situations within schools where the risk of transmission is higher. We report on measurements carried out in a French school (6-12 years children), where we collected data on the time-resolved face-to-face proximity of children and teachers using a proximity-sensing infrastructure based on radio frequency identification devices. Data on face-to-face interactions were collected on October 1st and 2nd, 2009. We recorded 77,602 contact events between 242 individuals. Each child has on average 323 contacts per day with 47 other children, leading to an average daily interaction time of 176 minutes. Most contacts are brief, but long contacts are also observed. Contacts occur mostly within each class, and each child spends on average three times more time in contact with classmates than with children of other classes. We describe the temporal evolution of the contact network and the trajectories followed by the children in the school, which constrain the contact patterns. We determine an exposure matrix aimed at informing mathematical models. This matrix exhibits a class and age structure which is very different from the homogeneous mixing hypothesis. The observed properties of the contact patterns between school children are relevant for modeling the propagation of diseases and for evaluating control measures. We discuss public health implications related to the management of schools in case of epidemics and pandemics. Our results can help define a prioritization of control measures based on preventive measures, case isolation, classes and school closures, that could reduce the disruption to education during epidemics.